Meet Teslim Olayiwola

I am a 4th year Chemical Engneering PhD candidate at the Louisiana State University, where I am advised by Professor Jose Romagnoli and Professor Revati Kumar. My research focus on multi-scale modeling of electrochemical systems leveraging tools such as numerical modeling, machine learning, optimization, and molecular dynamics. In the summer of 2023, I interned at Dow, where I developed machine learning solutions for surfactant formulation. Earlier in my PhD rotation, I worked briefly on intermetallic synthesis and catalyst regeneration.

Prior to joining the PhD program, I earned my Bachelor's degree in Chemical Engineering and Masters' degree in Petroleum Engineering from Ladoke Akintola University of Technology (LAUTECH) Nigeria and African University of Science and Technology (AUST) Nigeria, respectively.

During my undergraduate and graduate studies, I interned at Opex Oil and Gas Resources (assisgnment at Axxela) and Chevron Nigeria Limited, respectively. Also, I had a short research stinct at King Fahd University of Petroleum and Minerals (KFUPM) where I worked on molecular dynamics simulations of polymers and surfactant systems and atomistic study of the effect of maturity on water intake in kerogen. While working on these projects, I collaborated with other students and published scientific articles on side projects involving machine applications in petrophysical and fluid studies. I have been privileged to be advised by wonderful advisors: Professor Akeem Arinkoola at LAUTECH/AUST, Professor David Ogbe at AUST and Dr. Safwat Abdelazeim at KFUPM.

If you have questions or are interested in my work, please reach me at my email (tolayi1 at lsu dot edu). Actively seeking full-time (R&D and non-R&D) positions (resumption in Jan 2025) in the field of process engineering, data science, machine learning, AI and experiment (<15%). .

Resume  /  Google Scholar  /  GitHub  /  Linkedln  /  Twitter

At LSU

1. Synergizing data-driven and knowledge-based hybrid models for ionic separations
   Teslim Olayiwola, Luis Briceno-Mena,Christopher Arges, Jose Romagnoli
   ACS ES&T Engineering, 2024

2. Empowering capacitive devices: harnessing transfer learning for enhanced data-driven optimization
   Teslim Olayiwola, Revati Kumar, Jose A. Romagnoli
   ACS Industrial & Engineering Chemistry Research, 2024

3. Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis
   Miriam Nnadili, Andrew N. Okafor, Teslim Olayiwola, David Akinpelu, Revati Kumar, Jose A. Romagnoli
   ACS Industrial & Engineering Chemistry Research, 2024

4. Determining Ion Activity Coefficients in Ion-Exchange Membranes with Machine Learning and Molecular Dynamics Simulations
   Keshani Gallage Dona (equal), Teslim Olayiwola (equal), Luis Briceno-Mena, Christopher Arges, Revati Kumar & Jose Romagnoli
   Accepted in ACS Industrial & Engineering Chemistry Research, 2023

Before LSU

5. Smart and ensemble modeling of shear wave velocity using machine learning algorithms
   Teslim Olayiwola, Zeeshan Tariq, Abdulazeez Abdulraheem & Mohamed Mahmoud
   Neural Computing and Applications, 2022

6. Data-driven model for ternary-blend concrete compressive strength prediction using machine learning approach
   Babatunde Salami, Teslim Olayiwola, Tajudeen A Oyehan & Ishaq Raji
   Construction and Building Materials, 2021

7. Molecular simulation of kerogen-water interaction: Theoretical insights into maturity
   Lateef Lawal, Teslim Olayiwola, Safwat Abdel-Azeim, Mohamed Mahmoud, Abdulhamid Onawole & Shahzad Kamal
   Journal of Molecular Liquids, 2020

8. Modeling the acentric factor of binary and ternary mixtures of ionic liquids using advanced intelligent systems
   Teslim Olayiwola, Oghenerume Ogolo, Falola Yusuf
   Journal of Molecular Liquids, 2020

• XX/XXX: working on it.

Cloned P. Vadera's website.